CVE-2022-35989 : Exploit Details and Defense Strategies

TensorFlow, an open-source platform for machine learning, is impacted by a vulnerability in the

MaxPool

function that leads to a denial of service attack. Here's what you need to know about CVE-2022-35989 and how to address it.

Understanding CVE-2022-35989

This section provides detailed insights into the vulnerability affecting TensorFlow.

What is CVE-2022-35989?

TensorFlow is susceptible to a

CHECK

fail in the

MaxPool

function. Exploiting this issue can trigger a denial of service attack, posing a risk to affected systems.

The Impact of CVE-2022-35989

The vulnerability has a CVSS v3.1 base score of 5.9, with a medium severity. It has a high availability impact, making it essential to address promptly to prevent potential attacks.

Technical Details of CVE-2022-35989

Explore the specific technical aspects of CVE-2022-35989 below.

Vulnerability Description

When

MaxPool

receives a window size input array

ksize

with dimensions larger than its input tensor

input

, a

CHECK

fail occurs, which can be exploited for a denial of service attack.

Affected Systems and Versions

The vulnerability affects TensorFlow versions < 2.7.2, >= 2.8.0 and < 2.8.1, and >= 2.9.0 and < 2.9.1. It is crucial to ensure that systems running these versions are updated promptly.

Exploitation Mechanism

The GPU kernel triggers a

CHECK

fail when encountering the described condition, leading to the potential for attackers to exploit the vulnerability.

Mitigation and Prevention

Discover the essential steps to mitigate and prevent the CVE-2022-35989 vulnerability.

Immediate Steps to Take

Update affected TensorFlow versions to 2.10.0 to apply the patch and address the vulnerability. For systems running versions 2.7.2, 2.8.1, and 2.9.1, the patch will also be cherrypicked to provide protection.

Long-Term Security Practices

Incorporate robust security practices within your development and deployment processes to minimize the risk of similar vulnerabilities impacting your systems in the future.

Patching and Updates

Regularly monitor for security updates from TensorFlow and promptly apply patches to ensure that your systems are protected against known vulnerabilities.